Weather and electrical demand and consumption data of a small Mexican community

The development of novel technologies to mitigate the effects of climate change through Smart Grids requires energy related data. Unfortunately, this type of data is not always available in Mexico, especially from non-large urban areas and at the household level. Therefore, we present a dataset that contains electrical demand and consumption time series of 5 households within a small community in Mexico, at various resolutions, as well as weather data. The electrical demand is given in 15 min resolution, while the electrical consumption is presented in both hourly and daily resolutions. The data is contained within 15 separate .csv files; one for each household's resolution. In turn, the weather data is given in two .csv files (for outdoor and indoor variables, respectively) that together contain 24 meteorological variables measured in a 5 min resolution that is not always consistent. The dataset comprises of two separate folders that contain either the electrical demand and consumption files or the weather files. This dataset could aid in the development of novel smart grid methods and algorithms that might be able to push the energy transition in Mexico and other developing countries forward.


Energy data Weather data Smart grid a b s t r a c t
The development of novel technologies to mitigate the effects of climate change through Smart Grids requires energy related data.Unfortunately, this type of data is not always available in Mexico, especially from non-large urban areas and at the household level.Therefore, we present a dataset that contains electrical demand and consumption time series of 5 households within a small community in Mexico, at various resolutions, as well as weather data.The electrical demand is given in 15 min resolution, while the electrical consumption is presented in both hourly and daily resolutions.The data is contained within 15 separate .csvfiles; one for each household's resolution.In turn, the weather data is given in two .csvfiles (for outdoor and indoor variables, respectively) that together contain 24 meteorological variables measured in a 5 min resolution that is not always consistent.The dataset comprises of two separate folders that contain either the electrical demand and consumption files or the weather files.This dataset could aid in the development of novel smart grid methods and algorithms that might be able to push the energy transition in Mexico  The electrical demand and consumption data were measured using the Emporia Vue Smart Energy Monitor, with 50A circuit sensors .The sensors were installed in the electrical panels of each of the studied households and connected to their WiFi network.The sensors upload the information of the households' power demand and consumption to an online platform from which we can download the data.Furthermore, meteorological conditions were measured using the Ambient Weather WS-20 0 0 WiFi OSPREY Solar Powered Wireless Weather Station ; both its outdoor and indoor measuring units were installed in one of the monitored households.The weather station system measured 24 different variables and uploaded them to an online platform that allowed us to easily download them.

Value of the Data
• The presented dataset consists of the electrical demand and consumption time series of 5 households within a small community in the Mexican State of Puebla called Tepanco de López.This type of information is valuable, since time series of household power demand and consumption in resolutions as the ones presented are not easily accessible in Mexico.• The time series data can be used to develop, for instance, energy forecasting methods and grid control algorithms fine-tuned to the realities of a small community.• This information is also of value, as it may give researchers a better understanding of the time series data stemming from households within a small Mexican community.• The dataset also contains weather information measured directly in the community.Having both power and weather data can aid researchers simulate more realistic scenarios of the renewable energy integration in such a community.• The presented weather and electricity demand and consumption data can also be used to simulate the power consumption of buildings, to study how to reduce energy consumption, and to better understand the energy dynamics in small Mexican communities.

Data Description
The dataset includes information about electrical demand/consumption and meteorological data within a small community in the State of Puebla, presented in two different folders named electrical_demand_consumption , and weather.As their names suggest, the first folder contains the electrical demand and consumption information, while the other contains the corresponding cli- matological variables.In the following paragraphs, a geographical and climatological description is presented, as well as a more thorough description of the contents of each data folder.

Geographical and Climatological Overview
First, a general description of the municipality of Tepanco de López and its climatological information is presented.Tepanco de López is a municipality with an extension of 207.95 km2 located in the southern part of the state of Puebla, as shown in Fig. 1 [1] .The region exhibits three types of climates: sub-humid with summer rainfalls, tempered semiarid and warm semiarid.In terms of precipitation, the municipality is classified as Region III, with an annual average of 747.98 mm [2] .Finally, the annual average temperature ranges from 14 °C to 20 °C [3] .

Electrical Demand and Consumption Time Series
Within the electrical_demand_consumption folder there are fifteen .csvfiles containing time series of the electrical demand and consumption of five different households.Note that they are labeled as houseteh1, houseteh6, houseteh7, houseteh8, and houseteh10 2 .Within the folder there are three .csvfiles for each household; one containing the 15 min electrical demand measurements (in kW), another containing the 1 h electrical consumption values (in kWh), and a final one containing the daily electrical consumption measurements (in kWh).For the sake of clarity, these files have their resolution included in their names, for instance, the files containing information of the i th household would be named as housthei_15min.csv,housthei_1h.csv, and houstehi_1day.csv .Table 1 contains the label of each file and the description of its contents.Every file contains only two columns, the first one is named Time, in which the date and time are given using the dd/mm/yyyy HH:MM format, and a second one named after the unit of the values contained within the file (i.e., kW or kWh).Therefore, we can argue that data is given in the form of a time series.In principle, every file contains measurements from May 2022 to May 2023, nevertheless, since the different sensors were installed at different moments, their number of measurements might be different.Note that the household 7 files contain large amounts of missing values, due to an unexpected event that complicated the internet connection of that specific sensor.For all other households, except household 10, the only missing values are present on March 12th, 2023, due to the start of the daylight-saving time.Bear in mind that most of Mexico-including the state of Puebla-no longer observes the daylight-saving time (abolished in October 2022).It is important to mention that all missing values are labeled with a -1; these values do not stem from the sensors, but rather were added by us to make the identification of the missing values easier.For the sake of understanding, Table 2 contains the start and the end time of for every file measurement, as well as the number of data and missing values within it.

Time Series Representation
The information on electrical consumption and demand in each household is graphically represented on the heat maps of Figs.2-6 .Each figure contains an hourly average value of electrical consumption per weekday (left) and per month (right).This representation summarizes data that would be much more difficult to grasp if presented numerically [4] , therefore it is helpful to visualize the information and to identify preliminary patterns.

Weather Data
The weather data presented in this article is contained inside two .csvfiles named weather_outdoor variables.csvand weather_indoor variables.csvthat are found within the weather folder.Both files contain measurements from May 19th, 2022, to March 31st, 2023.The first file, weather_outdoor variables.csv,contains: Outdoor Temperature ( °C), Feels Like ( °C), Dew Point ( °C), Wind Speed (m/s), Wind Gust (m/s), Max Daily Gust (m/s), Wind Direction ( °), Hourly Rain (mm/h), Event Rain (mm), Daily Rain (mm), Weekly Rain (mm), Monthly Rain (mm), Yearly Rain (mm), Relative Pressure (hPa), Humidity (%), Ultra-Violet Radiation Index, Solar Radiation ( W/m 2 ) , Absolute Pressure (hPa), Avg Wind Direction (10 min) ( °), and Avg Wind Speed (10 min) (m/s).While the second file, weather_indoor variables.csv, contains: Indoor Temperature ( °C), Indoor Humidity (%), Indoor Feels Like ( °C), and Indoor Dew Point ( °C).Both files have a first column named Time, showing the date and time in which each measurement was taken using a dd/mm/yyyy HH:MM format; the names of the other columns stem from the measurements they contain.
The weather time series are given-approximately-in a 5 min resolution, yet the sampling of the measurements is not always consistent.It is important to mention that the data contains missing values, which could be more easily identified and corrected after a resampling that makes the 5 min resolution consistent.Furthermore, the dataset contains a large period of missing data starting on July 7th, 2022, at 15:35 and finishing on October 15th, 2022, at 10:41.
To visualize part of this dataset, a sample for the Temperature, Solar radiation and Humidity are represented, in Fig. 7 , for the month of November.

Experimental Design, Materials, and Methods
The Emporia Vue Smart Energy Monitor with 50A circuit sensors were used to measure the electrical demand and consumption of each household.These devices provide real-time measurements that can be accessed through the company's App or Website 3 .The sensor has a measurement range of 0.04 A to 75 A, with an Accuracy of ±2% and a resolution of 0.04 A or approx.5 W. The power demand and consumption in kW and kWh, respectively, is calculated from the measured values.
For the weather measurements, the Ambient Weather WS-20 0 0 WiFi OSPREY Solar Powered Wireless Weather Station4 was used.This system consists of an outdoor measuring station and an indoor measuring unit.The station for measuring the outdoor variables was installed outside household number 7, while the sensor for measuring indoor variables was placed inside.Both were connected to that household's internet.Once connected, they uploaded the weather data to an online platform from which the data could be easily downloaded in a .csvfile.Note that the outdoor measuring station was installed on top of a roof to obtain the best possible measurements without interference from surrounding buildings or objects.Please note that the specifications for measured parameters are given in Table 3 .It is important to mention that the weather values not contained in Table 3 are calculated from the ones that are measured.

Limitations
All the households present missing values for consumption and demand, as presented in Table 2 .To make their identification easier, the missing information is labeled with a -1 in every file.
The weather time series also contains missing values for a large period starting on July 7th, 2022, at 15:35 and finishing on October 15th, 2022, at 10:41.Furthermore, the sampling of the weather data is not always consistent.

Ethics Statement
The authors have read and follow the ethical requirements for publication in Data in Brief and confirm that the work does not involve human subjects, animal experiments or data collected from social media platforms.From the beginning, the electrical demand and consumption data was anonymized, thus the project approval committee did not consider an ethical approval necessary.Nevertheless, all participants were given an informed consent before the installation of the sensors, which they accepted and signed.

Data Availability
Electrical demand/consumption and climatological data of a small Mexican community (Original data) (Mendeley Data).

Table 1
File names and content description of the files contained within the electrical_demand_consumption folder.

Table 2
Start time, end time, number of measurements and number of missing values in every file within the electri-cal_demand_consumption folder.

Table 3
Weather measurement specifications taken from the products website4.Note that the values in the website are given in imperial units, which we converted to the SI units shown below.